Update docker GPU, avoid long build time (#1966)

Co-authored-by: Miro <mirhodak@amd.com>

graph/R-GAT/README.md

@@ -181,9 +181,10 @@ docker build . -f dockerfile.gpu -t rgat-gpu
 ```
 Run docker container:
 ```bash
-docker run --rm -it -v $(pwd):/root --gpus all rgat-gpu
+docker run --rm -it -v $(pwd):/workspace/root --gpus all rgat-gpu
 ```
-Run benchmark inside the docker container:
+Go inside the root folder and run benchmark inside the docker container:
 ```bash
+cd root
 python3 main.py --dataset igbh-dgl --dataset-path igbh/ --profile rgat-dgl-full --device gpu [--model-path <path_to_ckpt>] [--in-memory] [--dtype <fp16 or fp32>] [--scenario <SingleStream, MultiStream, Server or Offline>]
 ```

graph/R-GAT/dockerfile.gpu

@@ -26,6 +26,8 @@ RUN apt install -y --no-install-recommends rsync
 # Upgrade pip
 RUN python3 -m pip install --upgrade pip
 
+RUN pip install torch-geometric torch-scatter torch-sparse -f https://pytorch-geometric.com/whl/torch-2.1.0+cu121.html
+RUN pip install  dgl -f https://data.dgl.ai/wheels/torch-2.1/cu121/repo.html
 
 COPY requirements.txt requirements.txt
 RUN pip install -r requirements.txt
@@ -35,10 +37,6 @@ RUN cd /tmp && \
     pip install pybind11 && \
     CFLAGS="-std=c++14" python3 setup.py install
 
-RUN export TORCH_VERSION=$(python -c "import torch; print(torch.__version__)")
-RUN pip install torch-geometric torch-scatter torch-sparse -f https://data.pyg.org/whl/torch-${TORCH_VERSION}.html
-RUN pip install  dgl -f https://data.dgl.ai/wheels/torch-2.1/cu121/repo.html
-
 # Clean up
 RUN rm -rf mlperf \
     rm requirements.txt